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Record W2087672388 · doi:10.1038/sj.bjc.6603964

Colocalisation of CD9 and mortalin in CD9-induced mitotic catastrophe in human prostate cancer cells

2007· article· en· W2087672388 on OpenAlexafffund
V. Zvereff, J-C Wang, Kumehara Shun, Judith Lacoste, Mario Chevrette

Bibliographic record

VenueBritish Journal of Cancer · 2007
Typearticle
Languageen
FieldMedicine
TopicCell Adhesion Molecules Research
Canadian institutionsMcGill University Health CentreJewish General HospitalMcMaster University Medical CentreMcGill University
FundersCancer Research Society
KeywordsTetraspaninMitotic catastropheProstate cancerMitosisCancer researchCancer cellBiologyImmunoprecipitationCancerFusion proteinCellCell biologyImmunologyGeneAntibodyGenetics

Abstract

fetched live from OpenAlex

CD9, a member of the tetraspanin family of proteins, is involved in a variety of cellular interactions with many other proteins and molecules. Although CD9 has been implicated in cell fusion, migration and cancer progression, the detailed function of this protein is not completely understood and likely depends on interactions with different protein partners, which are not yet all known. Using co-immunoprecipitation and mass-spectrometric protein sequencing, we have identified in prostate cancer cells, a novel CD9 partner, the 75-kDa protein HSPA9B, also known as mortalin. We further show that introduction and overexpression of wild-type CD9 into human PC-3 prostate cancer cells induces mitotic catastrophe. We also demonstrate, by immunocolocalisation studies, the interaction of CD9 and mortalin in PC-3 cells undergoing mitotic catastrophe. Our results not only identified mortalin as a new CD9 partner, but also clarify the mechanisms by which CD9 may control prostate cancer progression.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.348
Teacher spread0.328 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations15
Published2007
Admission routes2
Has abstractyes

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